Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This book presents effective and time-saving recipes for leveraging the power of Python and putting it to use in the Spark ecosystem.
You'll start by learning about the Apache Spark architecture and seeing how to set up a Python environment for Spark. You'll then get familiar with the modules available in PySpark and start using them effortlessly. In addition to this, you'll discover how to abstract data with RDDs and DataFrames, and understand the streaming capabilities of PySpark. You'll then move on to using ML and MLlib in order to solve any problems related to the machine learning capabilities of PySpark, and you'll use GraphFrames to solve graph-processing problems. Finally, you will explore how to deploy your applications to the cloud using the spark-submit command.
By the end of this book, you will be able to use the Python API for Apache Spark to solve any problems associated with building data-intensive applications.
This book is for you if you are a Python developer looking for hands-on recipes for using the Apache Spark 2.x ecosystem in the best possible way. A thorough understanding of Python (and some familiarity with Spark) will help you get the best out of the book.
Chapter 1, Installing and Configuring Spark, shows us how to install and configure Spark, either as a local instance, as a multi-node cluster, or in a virtual environment.
Chapter 2, Abstracting Data with RDDs, covers how to work with Apache Spark Resilient Distributed Datasets (RDDs).
Chapter 3, Abstracting Data with DataFrames, explores the current fundamental data structure—DataFrames.
Chapter 4, Preparing Data for Modeling, covers how to clean up your data and prepare it for modeling.
Chapter 5, Machine Learning with MLlib, shows how to build machine learning models with PySpark's MLlib module.
Chapter 6, Machine Learning with the ML Module, moves on to the currently supported machine learning module of PySpark—the ML module.
Chapter 7, Structured Streaming with PySpark, covers how to work with Apache Spark structured streaming within PySpark.
Chapter 8, GraphFrames – Graph Theory with PySpark, shows how to work with GraphFrames for Apache Spark.
You need the following to smoothly work through the chapters:
- Apache Spark (downloadable from http://spark.apache.org/downloads.html)
- Python
You can download the example code files for this book from your account at www.packtpub.com. If you purchased this book elsewhere, you can visit www.packtpub.com/support and register to have the files emailed directly to you.
You can download the code files by following these steps:
- Log in or register at www.packtpub.com.
- Select the
SUPPORTtab. - Click on
Code Downloads & Errata. - Enter the name of the book in the
Searchbox and follow the onscreen instructions.
Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:
- WinRAR/7-Zip for Windows
- Zipeg/iZip/UnRarX for Mac
- 7-Zip/PeaZip for Linux
The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/PySpark-Cookbook. In case there's an update to the code, it will be updated on the existing GitHub repository.
We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: https://www.packtpub.com/sites/default/files/downloads/PySparkCookbook_ColorImages.pdf.
There are a number of text conventions used throughout this book.
CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "Next, we call three functions: printHeader, checkJava, and checkPython."
A block of code is set as follows:
if [ "${_check_R_req}" = "true" ]; then
checkR
fiWhen we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
if [ "$_machine" = "Mac" ]; then
curl -O $_spark_source
elif [ "$_machine" = "Linux"]; then
wget $_spark_sourceAny command-line input or output is written as follows:
tar -xvf sbt-1.0.4.tgz sudo mv sbt-1.0.4/ /opt/scala/
Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "Go to File | Import appliance; click on the button next to the path selection."
In this book, you will find several headings that appear frequently (Getting ready, How to do it..., How it works..., There's more..., and See also).
To give clear instructions on how to complete a recipe, use these sections as follows:
This section tells you what to expect in the recipe and describes how to set up any software or any preliminary settings required for the recipe.
This section usually consists of a detailed explanation of what happened in the previous section.
This section consists of additional information about the recipe in order to make you more knowledgeable about the recipe.
Feedback from our readers is always welcome.
General feedback: Email [email protected] and mention the book title in the subject of your message. If you have questions about any aspect of this book, please email us at [email protected].
Errata: Although we have taken every care to ensure the accuracy of our content, mistakes do happen. If you have found a mistake in this book, we would be grateful if you would report this to us. Please visit www.packtpub.com/submit-errata, selecting your book, clicking on the Errata Submission Form link, and entering the details.
Piracy: If you come across any illegal copies of our works in any form on the internet, we would be grateful if you would provide us with the location address or website name. Please contact us at [email protected] with a link to the material.
If you are interested in becoming an author: If there is a topic that you have expertise in and you are interested in either writing or contributing to a book, please visit authors.packtpub.com.
Please leave a review. Once you have read and used this book, why not leave a review on the site that you purchased it from? Potential readers can then see and use your unbiased opinion to make purchase decisions, we at Packt can understand what you think about our products, and our authors can see your feedback on their book. Thank you!
For more information about Packt, please visit packtpub.com.